Embodied AI: World Models Research Engineer

Orbifold AI, Inc.; Palo Alto, Northern (CA, KY); Hybrid; USD 140,000 - 230,000; Full time

Job summary

Orbifold AI, Inc. is seeking a Research Engineer to advance world models and simulation for robotic policies. You will develop learned environments from real-captured data and design evaluation harnesses to stress-test policies.

You will train generative world models, generate targeted synthetic data, and scale multi-node PyTorch workflows. You’ll work with a founding team to push the boundaries of embodied intelligence in physics-rich simulation.

Qualifications

• PhD or equivalent research experience, with first-author publications or shipped work in one of: world models and action-conditioned video generation, video diffusion or autoregressive video models, model-based RL, neural rendering and reconstruction, robot learning in simulation.
• Strong ML engineering, PyTorch, distributed training, and at least one project where infrastructure was genuinely part of the research problem.
• A specific, clear-eyed view of where generated data stops being useful. We would rather hire someone who can say precisely what their model gets wrong.
• Comfortable being measured on whether a partner’s real-world policy improved, not on a generation benchmark alone.
• Self-driven and high agency, with experience in fast-paced applied research or startup environments.
• We index on the quality of the work rather than years served. A recent PhD with strong first-author publications in a directly relevant area is exactly who we want to talk to.

Responsibilities

• Train generative world models on a corpus of real-world data to evaluate policies.
• Generate targeted synthetic data aimed at specific deficits to improve downstream policies.
• Build rollout and evaluation harnesses: scenarios, scoring, reproducible runs, reporting to research leads.
• Measure the reality gap rigorously and publish internally to drive data collection.
• Work with classical simulation where it earns its place: Isaac Sim/Lab, MuJoCo, Genesis, ManiSkill.
• Scale training with multi-node PyTorch on Ray, treating throughput as a research problem.

Skills

PyTorch

Distributed training

Research background

First-author publications

Education

PhD or equivalent research experience

Job description

Orbifold AI, Inc. is seeking a Research Engineer to advance world models and simulation for robotic policies. You will develop learned environments from real-captured data and design evaluation harnesses to stress-test policies.

You will train generative world models, generate targeted synthetic data, and scale multi-node PyTorch workflows. You’ll work with a founding team to push the boundaries of embodied intelligence in physics-rich simulation.